A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

Linking unfounded beliefs to genetic dopamine availability

Unfounded convictions involving beliefs in the paranormal, grandiosity ideas or suspicious thoughts are endorsed at varying degrees among the general population. Here, we investigated the neurobiopsychological basis of the observed inter-individual variability in the propensity toward unfounded beliefs. One hundred two healthy individuals were genotyped for four polymorphisms in the COMT gene (rs6269, rs4633, rs4818, and rs4680, also known as val158met) that define common functional haplotypes with substantial impact on synaptic dopamine degradation, completed a questionnaire measuring unfounded beliefs, and took part in a behavioral experiment assessing perceptual inference. We found that greater dopamine availability was associated with a stronger propensity toward unfounded beliefs, and that this effect was statistically mediated by an enhanced influence of expectations on perceptual inference. Our results indicate that genetic differences in dopaminergic neurotransmission account for inter-individual differences in perceptual inference linked to the formation and maintenance of unfounded beliefs. Thus, dopamine might be critically involved in the processes underlying one's interpretation of the relationship between the self and the world

A multimodal neuroimaging classifier for alcohol dependence

With progress in magnetic resonance imaging technology and a broader dissemination of state-of-the-art imaging facilities, the acquisition of multiple neuroimaging modalities is becoming increasingly feasible. One particular hope associated with multimodal neuroimaging is the development of reliable data-driven diagnostic classifiers for psychiatric disorders, yet previous studies have often failed to find a benefit of combining multiple modalities. As a psychiatric disorder with established neurobiological effects at several levels of description, alcohol dependence is particularly well-suited for multimodal classification. To this aim, we developed a multimodal classification scheme and applied it to a rich neuroimaging battery (structural, functional task-based and functional resting-state data) collected in a matched sample of alcohol-dependent patients (N = 119) and controls (N = 97). We found that our classification scheme yielded 79.3% diagnostic accuracy, which outperformed the strongest individual modality - grey-matter density - by 2.7%. We found that this moderate benefit of multimodal classification depended on a number of critical design choices: a procedure to select optimal modality-specific classifiers, a fine-grained ensemble prediction based on cross-modal weight matrices and continuous classifier decision values. We conclude that the combination of multiple neuroimaging modalities is able to moderately improve the accuracy of machine-learning-based diagnostic classification in alcohol dependence

Neurobiological basis of interindividual differences in visual perception

Das Erzeugen einer stabilen und kohärenten Wahrnehmung unserer externen Umwelt stellt eine Herausforderung für unser visuelles System dar. Die uneindeutigen und verrauschten sensorischen Signale (bottom-up) werden hierbei mit Vorhersagen (top-down) integriert. Dieser, als perzeptuelle Inferenz bezeichnete Prozess, kann mittels bistabiler Wahrnehmungsexperimente untersucht werden. Bistabile Reize weisen uneindeutige physikalische Eigenschaften zweier sich ausschließenden Interpretationen auf und erzeugen persistierende Wahrnehmungswechsel. Die vorliegende Dissertation untersucht die interindividuelle Variabilität bistabiler Wahrnehmung hinsichtlich verschiedener genetischer, neurobiologischer und kognitiver Einflussfaktoren, um zu einem besseren Verständnis von perzeptuellen Inferenzmechanismen als zentralem Bestandteil in Pathogenesemodellen der bipolaren affektiven Störung und der Schizophrenie beizutragen. In der ersten Studie wurden funktionelle dopaminassoziierte Varianten zweier Kandidatengene der bipolaren Störung (DRD4, DAT1) mit perzeptueller Stabilität in Verbindung gebracht, wobei das Risiko-Allel DRD4-2R mit einer stabileren Perzeption einherging. In der zweiten Arbeit wurde die funktionelle Magnetresonanztomographie (fMRT) genutzt um neuronale Korrelate kognitiver Erwartungen in der perzeptuellen Inferenz zu bestimmen und diese mit Wahnsymptomatik zu verbinden. Hierbei ging eine verringerte perzeptuelle Stabilität mit verstärkten wahnhaften Überzeugungen und einem größeren Erwartungseffekt auf die visuelle Wahrnehmung einher, der als stärkere topdown Modulation präfrontaler Gehirnareale auf den primären visuellen Kortex identifiziert wurde. In der dritten Arbeit wurde die dopaminerge Bioverfügbarkeit mittels funktioneller Genvarianten der Catechol-O-Methyltransferase (COMT) mit der Tendenz zu wahnhaften Überzeugungen und dem Erwartungseffekt auf die Wahrnehmung in Verbindung gesetzt. Dabei zeigte sich, dass höhere Dopaminspiegel mit Wahnsymptomatik korrelierten und dieser Zusammenhang durch den perzeptuellen Erwartungseffekt vermittelt wurde. In der abschließenden Studie wurden mittels fMRT neuronale Korrelate kognitiver Flexibilität mit interindividuellen Unterschieden der perzeptuellen Inferenz in Beziehung gesetzt. Die gefundene Korrelation von perzeptueller Stabilität mit kognitiver, flexibilitäts-abhängiger neuronaler Aktivität in den Basalganglien deutet darauf hin, dass fronto-striatale Gehirnareale auch bei der visuellen Wahrnehmung von Relevanz sind. Zusammenfassend etabliert die vorliegende Arbeit eine Beteiligung des Dopaminsystems bei perzeptuellen Inferenzmechanismen und impliziert über den Zusammenhang mit Wahnsymptomatik eine wichtige Rolle in der Pathogenese der Schizophrenie. Zudem konnten erstmalig die bisher separat betrachteten Inferenzprozesse in Kognition und Perzeption als zusammenhängende und generelle integrative Mechanismen unseres Gehirns etabliert werden.Maintaining a stable and unique experience of the world is a constant challenge to our visual system. As sensory data are often noisy, visual perception can be described as an inferential process that combines bottom-up sensory input with top-down predictions. This process of perceptual inference can be assessed using ambiguous stimuli that cause our perception to continuously switch between two mutually exclusive interpretations. The current dissertation investigated the impact of several genetic, neurobiological and cognitive factors on interindividual differences in visual perception, in order to broaden the understanding of perceptual inference as a central feature in the pathogenesis of bipolar affective disorder and schizophrenia. In the first study we tested the association of two dopamine-associated candidate genes for bipolar disorder with functional impact on dopaminergic neurotransmission (DRD4, DAT1) with perceptual stability. We found the risk-allel DRD4-2R to be significantly associated with a more stable perception. In the second study functional magnetic resonance imaging (fMRI) was used to identify the neural correlates of top-down predictions on visual perception and to relate effects of learned expectations of perception to individuals’ tendency towards unfounded beliefs. Participants with decreased perceptual stability had higher delusion scores and their perception was more strongly influenced by experimentally induced beliefs that were identified as increased prefrontal top-down modulation on primary visual areas. The third study investigated whether the tendency towards delusional conviction depended on dopaminergic neurotransmission by assessing a functional haplotype of Catechol-O-Methyltransferase (COMT). It was shown that substantially increased synaptic dopamine levels are not only associated with stronger delusion conviction, but also correlated with the degree of belief-induced bias on perception. The correlation between dopamine-levels and delusion conviction was shown to be mediated by the degree of the belief-induced bias on perception. In the last study fMRI was used to interrelate the neural correlates of cognitive flexibility with inter-individual differences in perceptual inference. Perceptual flexibility correlated with cognitive flexibility-associated activity in the right putamen as part of the basal ganglia. This points towards a relevance of fronto-striatal brain areas in visual perception. Taken together, this thesis proves the involvement of the dopaminergic system in the inferential processes of visual perception. The associations of delusional ideations with perceptual inference suggests an important role of the latter in the pathogenesis of schizophrenia. Further empirical support is provided for the general notion of shared mechanisms between perception and cognition

Spectral EEG abnormalities during vibrotactile encoding and quantitative working memory processing in schizophrenia

Schizophrenia is associated with a number of cognitive impairments such as deficient sensory encoding or working memory processing. However, it is largely unclear how dysfunctions on these various levels of cortical processing contribute to alterations of stimulus-specific information representation. To test this, we used a well-established sequential frequency comparison paradigm, in which sensory encoding of vibrotactile stimuli can be assessed via frequency-specific steady-state evoked potentials (SSEPs) over primary somatosensory cortex (S1). Further, we investigated the maintenance of frequency information in working memory (WM) in terms of parametric power modulations of induced beta-band EEG oscillations. In the present study schizophrenic patients showed significantly less pronounced SSEPs during vibrotactile stimulation than healthy controls. In particular, inter-trial phase coherence was reduced. While maintaining vibrotactile frequencies in WM, patients showed a significantly weaker prefrontal beta-power modulation compared to healthy controls. Crucially, patients exhibited no general disturbances in attention, as inferred from a behavioral test and from alpha-band event-related synchronization. Together, our results provide novel evidence that patients with schizophrenia show altered neural correlates of stimulus-specific sensory encoding and WM maintenance, suggesting an early somatosensory impairment as well as alterations in the formation of abstract representations of task-relevant stimulus information

No evidence for abnormal priors in early vision in schizophrenia

The predictive coding account of psychosis postulates the abnormal formation of prior beliefs in schizophrenia, resulting in psychotic symptoms. One domain in which priors play a crucial role is visual perception. For instance, our perception of brightness, line length, and motion direction are not merely based on a veridical extraction of sensory input but are also determined by expectation (or prior) of the stimulus. Formation of such priors is thought to be governed by the statistical regularities within natural scenes. Recently, the use of such priors has been attributed to a specific set of well-documented visual illusions, supporting the idea that perception is biased toward what is statistically more probable within the environment. The Predictive Coding account of psychosis proposes that patients form abnormal representations of statistical regularities in natural scenes, leading to altered perceptual experiences. Here we use classical vision experiments involving a specific set of visual illusions to directly test this hypothesis. We find that perceptual judgments for both patients and control participants are biased in accordance with reported probability distributions of natural scenes. Thus, despite there being a suggested link between visual abnormalities and psychotic symptoms in schizophrenia, our results provide no support for the notion that altered formation of priors is a general feature of the disorder. These data call for a refinement in the predictions of quantitative models of psychosis